< BACK Unveiling the Future of Psoriatic Arthritis Care: Insights from Dr Laura Coates Mar 19, 2024 Exploring the iPROLEPSIS Project and Innovations in Digital Health Technologies for Enhanced Patient Care Dr Laura Coates , a researcher and clinician from the University of Oxford , guides through the research and clinical studies of the iPROLEPSIS project. In her own words: "It’s my pleasure to be leading all of the clinical studies within the iPROLEPSIS Consortium. We're focused on developing and testing apps and digital health technologies to enhance the care for patients with psoriatic arthritis ." Discover how these innovative tools aim to predict and manage psoriatic arthritis flares, identify at-risk individuals, and empower patients to take control of their health. Dr Coates elaborates on the various aspects of the research, including the development of apps that could foresee a flare, identify triggers, and even provide support for stress management and activity. https://www.youtube.com/watch?v=nYPtH0jb0yo Screenshot 2024-03-19 123331.png Screenshot 2024-03-19 123331.png 1/1 PREVIOUS NEXT

< BACK Advancing Psoriatic Arthritis: Rheumatologist Ilja Tchetverikov's Insights on iPROLEPSIS May 22, 2024 Exploring Innovative Approaches to Disease Management and Patient Care in Psoriatic Arthritis" Ilja Tchetverikov , a rheumatologist and project partner from the CICERO Foundation (the Netherlands), provides insights into the iPROLEPSIS project's endeavours. He emphasises the need for a deeper understanding of psoriatic arthritis , a chronic inflammatory condition impacting various body parts due to immune system disturbances. I. Tchetverikov highlights the project's focus on investigating disease progression factors and developing non-invasive measurement tools . “Everybody can measure anything, but then you have to know what you're measuring. The whole idea of the project is that we combine two strengths. One of them is providing and developing a technical solution on how to measure the disease activity. And from the other side, we are going to label the data coming in from the system, from the clinical point of view. So we will be able to say whether or not some people have a low or high level of disease activity. So it's one part of the investigation. The other part of the investigation is to see whether other factors, which are already known to influence the whole system of your human body, like stress factors and some, for instance, gut microbiome composition, can also change during the course of the disease and how they are influencing the course of the disease itself,” states Ilja Tchetverikov . Through a collaborative effort integrating clinical expertise and technical innovation, the project aims to assess disease activity levels and explore external factors accurately. https://www.youtube.com/watch?v=PcUHfHsWSVs iPROLEPSIS interview.png iPROLEPSIS interview.png 1/1 PREVIOUS NEXT

< BACK iPROLEPSIS at BIOSTEC 2026 Mar 16, 2026 Presenting iPROLEPSIS at an international forum on biomedical engineering and health technology The 19th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2026) took place in Marbella, Spain from 2 to 4 March 2026. The event brought together researchers, technology developers, and industry representatives working in biomedical engineering and healthcare technologies. iPROLEPSIS was represented at the event by project partner PLUX. The project was presented to an international audience, helping to raise its visibility among stakeholders interested in digital health and innovative medical technologies. PLUX also highlighted the importance of multisensor biosignal acquisition and the value of combining different physiological signals to support more comprehensive health research and real-world healthcare applications. iProlepsis BIOSTEC 2.jpg 20260303_111530.jpg IMG_6609.jpg iProlepsis BIOSTEC 2.jpg 1/4 PREVIOUS NEXT

< BACK AI-Driven Early Prediction and Personalised Care | iPROLEPSIS, AI-PROGNOSIS & REBECCA Mar 3, 2026 A joint video highlighting how digital biomarkers and real-world data support patient-centred healthcare across three disease areas What happens when a disease enters someone’s life and changes everything? Millions of people live with chronic conditions that shape their daily routines – often in ways that are invisible to others. Early diagnosis, timely intervention and more effective care can make a profound difference. In a new joint video developed with support from the European Commission’s Booster initiative, the EU-funded projects iPROLEPSIS , AI-PROGNOSIS and REBECCA present a shared vision for patient-centred artificial intelligence in healthcare. The video highlights how AI and digital biomarkers can enable earlier prediction, continuous monitoring and more personalised care across three disease areas: Psoriatic arthritis (iPROLEPSIS) Parkinson’s disease (AI-PROGNOSIS) Breast cancer survivorship (REBECCA) By integrating real-world behavioural data, wearable sensor signals and patient-reported information, the projects demonstrate how complex health data can be transformed into actionable clinical insights. These AI-driven approaches aim to strengthen clinical decision-making while keeping patients at the centre of care. The video reflects the projects’ commitment to developing trustworthy, responsible and co-designed AI solutions that respond to real clinical and patient needs. Watch the video here: https://www.youtube.com/watch?v=hWu3bPzQBiA To learn more, visit: iPROLEPSIS – https://www.iprolepsis.eu AI-PROGNOSIS – https://www.ai-prognosis.eu REBECCA – https://www.rebeccaproject.eu Screenshot 2026-03-02 115452.png Screenshot 2026-03-02 115452.png 1/1 PREVIOUS NEXT

Learning Hub Explore resources to help you understand and manage psoriatic arthritis. Learning hub Key Facts Handbook News Feed Quizzes Search What is psoriatic arthritis? See related Handbook section PREVIOUS NEXT

< BACK Dynamic Difficulty Adjustment in Psoriatic Arthritis Serious Games Using Learning-Driven Policies Sep 1, 2026 New iPROLEPSIS publication presents machine learning approach to personalise game difficulty based on patient condition A new iPROLEPSIS publication presents a system that automatically adjusts game difficulty to match each patient's changing condition during therapeutic gameplay. The study proposes a Dynamic Difficulty Adjustment (DDA) system using machine learning – specifically Reinforcement Learning and Multi-Armed Bandits –to personalise how two serious games challenge players: Mr. Blue Sky, targeting wrist mobility, and The Kite, focusing on breathing and relaxation. Data were collected from 32 participants playing these games, tracking gameplay performance, physiological signals (heart rate and stress), and self-reported relaxation levels. Machine learning algorithms learned which difficulty progression works best based on how patient condition changes during play. Results showed that the best-performing strategies began gameplay at medium difficulty, then adjusted downward. In a feasibility pilot with six psoriatic arthritis patients, this automatic adjustment produced coherent therapeutic progressions while accounting for the fluctuating nature of patient symptoms. The system demonstrates how machine learning can support personalised rehabilitation, continuously adapting game challenges to patient needs rather than using fixed difficulty levels. Read the full publication: https://ieeexplore.ieee.org/document/11663158 iPROLEPSIS_Dynamic Difficulty adjustment in PsA publication.png iPROLEPSIS_Dynamic Difficulty adjustment in PsA publication.png 1/1 PREVIOUS NEXT

< BACK Season's Greetings from iPROLEPSIS Dec 21, 2023 Merry Christmas and Happy New Year! No updates and announcements, simply warmth, joy, health and peace from the iPROLEPSIS consortium to all our community! Thank you for being a part of our journey. merry (1).png merry (1).png 1/1 PREVIOUS NEXT

< BACK iPROLEPSIS at IEEE-EMBS BSN 2025 Nov 6, 2025 Showcasing iPROLEPSIS at a leading international conference on body sensor research The IEEE-EMBS International Conference on Body Sensor Networks (IEEE-EMBS BSN 2025) took place in Los Angeles, USA, from 3–5 November 2025. The conference brings together researchers, clinicians, and industry representatives working on body sensor technologies and their applications in health and biomedical research. iPROLEPSIS was showcased at the event by project partner PLUX , which hosted a dedicated booth. The project was presented to an international audience, increasing its visibility within the body sensor and digital health research community. IEEE EMBS 2025 2.HEIC IEEE EMBS 2025 1.HEIC IEEE EMBS 2025 3.HEIC IEEE EMBS 2025 2.HEIC 1/3 PREVIOUS NEXT

< BACK iPROLEPSIS at GRAPPA 2025: Advancing Digital Tools for Psoriatic Arthritis Care Jul 18, 2025 Exploring how digital biomarkers can support hand function assessment in real-world settings iPROLEPSIS participated in the GRAPPA Annual Meeting 2025 , held on 10–12 July in Bogotá, Colombia. Vasilis Charisis (Aristotle University of Thessaloniki – AUTH) presented an overview of the project’s key objectives and emerging results. The talk highlighted how digital biomarkers – captured via smartphone typing dynamics and video-based motor tasks – can support the assessment of hand function in real-world conditions. The session reached approximately 350 stakeholders, including clinicians, researchers, and industry representatives, helping raise awareness of iPROLEPSIS and its goals within the psoriatic disease community. 2.jpg 1.jpg 3.jpg 2.jpg 1/3 PREVIOUS NEXT

< BACK iPROLEPSIS at IEEE HealthCom 2025: AI-Enabled Digital Health for Psoriatic Arthritis Nov 3, 2025 Project researchers presented new studies, co-chaired a workshop, and joined a panel on digital innovation in healthcare in Abu Dhabi The iPROLEPSIS team participated in the IEEE HealthCom 2025 Conference , held 21–23 October 2025 and hosted by Khalifa University in Abu Dhabi, United Arab Emirates . The event gathered international experts in digital health , artificial intelligence , and biomedical technologies to discuss how AI can improve the understanding and management of non-communicable diseases . Modeling joint swelling through smartphone photographs Giorgos Apostolidis from the Signal Processing & Biomedical Technology Unit – AUTH presented the paper “Modeling Interphalangeal Joints for Swelling Assessment in Psoriatic Arthritis via Smartphone Photographs”. By analyzing smartphone photos of hands, the study showcased that a digital estimation of joint thickness, namely effective width , with the aid of a logistic regression model , can serve as an effective tool for detecting interphalangeal joint swelling in people with PsA .This approach was validated on a real-world dataset collected within the PDPID study . Giorgos Apostolidis (Signal Processing & Biomedical Technology Unit – AUTH) Designing exergames for Psoriatic Arthritis care Prof. Leontios Hadjileontiadis (AUTH) presented the paper “Designing Exergames for Psoriatic Arthritis: The Spy and Zen Forest Paradigms”. The Spy and Zen Forest exergames were co-designed to complement PsA care by making therapeutic exercises more engaging and accessible at home. Using real-time body tracking on mobile devices , these games promote dynamic movement to enhance mobility and strength, and calm stretching for flexibility and relaxation. Prof. Leontios Hadjileontiadis (Signal Processing & Biomedical Technology Unit-AUTH) Panel discussion: Digital Bridges for Better Health Project Coordinator Prof. Leontios Hadjileontiadis , Scientific & Technical Manager Vasileios Charisis , and Stelios Hadjidimitriou from the Signal Processing & Biomedical Technology Unit – AUTH , together with Dr. Kosmas Dimitropoulos from the Centre for Research & Technology Hellas (CERTH) and Prof. Mohamed Seghier from Khalifa University , participated in the panel discussion “Digital Bridges for Better Health: AI Innovation from Europe to the Middle East and North Africa (MENA),” moderated by Giorgos Apostolidis. The panel provided insights into: The technical challenges in integrating AI with existing healthcare IT systems, How key stakeholders can collaborate to ensure AI digital health tools are user-friendly and clinically relevant, The role of patient engagement and digital literacy in the effectiveness of AI tools in chronic disease management How socio-cultural differences between Europe and MENA can influence the design and adoption of AI digital health solutions What are the key regulatory challenges in Europe and MENA regarding the use of AI in healthcare and what joint efforts can be undertaken to harmonize standards in these regions During the session, the iPROLEPSIS project and its AI-enabled digital health tools for assisting Psoriatic Arthritis management and care were highlighted as a case study of AI solutions with potential to improve outcomes for people with non-communicable diseases . Panel discussion "Digital Bridges for better health: AI Innovation from Europe to the Middle East and North Africa (MENA)" Workshop chairing Scientific & Technical Manager Vasileios Charisis from the Signal Processing & Biomedical Technology Unit-AUTH co-chaired the workshop "AI-enabled Digital Health Tools for Non-Communicable Diseases: From Concepts to Impact" . The workshop was co-organised with the AI-PROGNOSIS Horizon Europe project and included research works in the fields of psoriatic arthritis, Parkinson's disease, multiple sclerosis and post-stroke rehabilitation. Two of the presented papers stem from research carried out within iPROLEPSIS: Apostolidis et al., Modeling Interphalangeal Joints for Swelling Assessment in Psoriatic Arthritis via Smartphone Photographs Ramalho et al., Designing exergames for psoriatic arthritis: The Spy and Zen Forest paradigms Workshop “AI-enabled Digital Health Tools for Non-Communicable Diseases: From Concepts to Impact” The iPROLEPSIS and AI-PROGNOSIS teams from AUTH participated jointly at IEEE HealthCom 2025 , highlighting their shared commitment to advancing AI-enabled digital health solutions that enhance the understanding, early detection, and management of chronic diseases . iPROLEPSIS and AI-PROGNOSIS team members PXL_20251021_131742947.MP.jpg 2.jpg IMG_2954.jpg PXL_20251021_131742947.MP.jpg 1/11 PREVIOUS NEXT

< BACK iPROLEPSIS, AI-PROGNOSIS & REBECCA: A Thematic Cluster on AI-Driven Digital Health Jul 17, 2025 Three EU-funded projects exploring real-world data, wearables, and personalised care in healthcare innovation Have you ever asked yourself how to make AI really effective along the patient journey? That was one of the first questions we asked ourselves when we launched our project. Along the way, we discovered we weren’t alone – many other research initiatives working with AI in healthcare were asking the same thing. That’s why we decided to take a step forward and create a cluster : a concrete way to collaborate, foster the impact of our solutions, and improve them through scientific exchange and an open science approach. AI-PROGNOSIS, iPROLEPSIS, and REBECCA – three EU-funded projects to advance patient-centric AI in healthcare. Focusing on Parkinson’s disease (PD), AI-PROGNOSIS is developing a suite of AI-powered tools for both patients and clinicians . These include early risk assessment, symptom monitoring, and medication support – based on real-world data from wearables and patient self-reports. It’s about enabling timely, data-driven decisions and bringing predictive analytics to the heart of primary care. iPROLEPSIS is building a comprehensive digital health ecosystem for psoriatic arthritis (PsA). It brings together a multisource biobank, a smartphone-based app powered by digital biomarkers and AI-driven predictive models, and an intervention module featuring therapeutic games, lifestyle coaching, and sleep support. The goal? To reshape the way we monitor and treat chronic inflammatory diseases through personalised mobile health solutions. Finally, REBECCA is working to improve long-term care for breast cancer survivors. By combining electronic health records with data from wearables and behaviour tracking , it generates real-world evidence on patients’ emotional, functional, and quality-of-life needs. Its explainable AI platform also supports caregivers and families via a dedicated app, empowering a more holistic approach to survivorship. What will we do together? We aim to contribute to the discussion on how AI-based digital health can support medical decision-making and real-time monitoring within daily hospital routines. I ntegrating AI into clinical practice is no easy task. Our solutions are designed to enable real-time health monitoring, informed decision-making, and disease management by leveraging biometric, behavioral, and clinical data –maximizing the impact along the patient journey. Another area of strong interest is the development of digital infrastructures that integrate wearable, clinical, behavioral, and environmental datasets. We believe these can be analyzed collectively through AI to generate real-world evidence and support both predictive and causal modeling – helping to guide research and inform treatment planning in more meaningful ways. Cluster.png Cluster.png 1/1 PREVIOUS NEXT

< BACK AINIGMA Technologies at InnoHealth Forum 2024 Sep 24, 2024 Highlights from InnoHealth Forum 2024 iPROLEPSIS colleagues from the AINIGMA Technologies team participated in the InnoHealth Forum 2024 (20-21 September, 2024), an event that promotes and highlights innovative health technology solutions for the benefit of humanity. With 25 exhibitors, 50+ live demos of cutting-edge health products and services and over 130 matchmaking meeting and networking opportunities, this forum was a great opportunity to spread the word about the iPROLEPSIS project and connect with potential end-users. 1/5 PREVIOUS NEXT